Overview

Dataset statistics

Number of variables18
Number of observations5000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory703.2 KiB
Average record size in memory144.0 B

Variable types

Boolean3
Numeric15

Alerts

numbervmailmessages is highly overall correlated with voicemailplanHigh correlation
totaldayminutes is highly overall correlated with totaldaychargeHigh correlation
totaldaycharge is highly overall correlated with totaldayminutesHigh correlation
totaleveminutes is highly overall correlated with totalevechargeHigh correlation
totalevecharge is highly overall correlated with totaleveminutesHigh correlation
totalnightminutes is highly overall correlated with totalnightchargeHigh correlation
totalnightcharge is highly overall correlated with totalnightminutesHigh correlation
totalintlminutes is highly overall correlated with totalintlchargeHigh correlation
totalintlcharge is highly overall correlated with totalintlminutesHigh correlation
voicemailplan is highly overall correlated with numbervmailmessagesHigh correlation
internationalplan is highly imbalanced (54.8%)Imbalance
numbervmailmessages has 3678 (73.6%) zerosZeros
numbercustomerservicecalls has 1023 (20.5%) zerosZeros

Reproduction

Analysis started2023-03-25 04:05:54.079049
Analysis finished2023-03-25 04:06:38.811364
Duration44.73 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

churn
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
False
4293 
True
707 
ValueCountFrequency (%)
False 4293
85.9%
True 707
 
14.1%
2023-03-25T09:36:38.987770image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

accountlength
Real number (ℝ)

Distinct218
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.2586
Minimum1
Maximum243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:39.144011image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile35
Q173
median100
Q3127
95-th percentile167
Maximum243
Range242
Interquartile range (IQR)54

Descriptive statistics

Standard deviation39.69456
Coefficient of variation (CV)0.39592174
Kurtosis-0.10162108
Mean100.2586
Median Absolute Deviation (MAD)27
Skewness0.10929112
Sum501293
Variance1575.6581
MonotonicityNot monotonic
2023-03-25T09:36:39.331507image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90 65
 
1.3%
87 59
 
1.2%
105 57
 
1.1%
93 57
 
1.1%
112 56
 
1.1%
101 55
 
1.1%
100 55
 
1.1%
86 55
 
1.1%
116 54
 
1.1%
103 54
 
1.1%
Other values (208) 4433
88.7%
ValueCountFrequency (%)
1 11
0.2%
2 2
 
< 0.1%
3 8
0.2%
4 3
 
0.1%
5 2
 
< 0.1%
6 2
 
< 0.1%
7 5
0.1%
8 2
 
< 0.1%
9 3
 
0.1%
10 3
 
0.1%
ValueCountFrequency (%)
243 1
 
< 0.1%
238 1
 
< 0.1%
233 1
 
< 0.1%
232 2
< 0.1%
225 2
< 0.1%
224 2
< 0.1%
222 2
< 0.1%
221 1
 
< 0.1%
217 3
0.1%
216 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
False
4527 
True
473 
ValueCountFrequency (%)
False 4527
90.5%
True 473
 
9.5%
2023-03-25T09:36:39.503379image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
False
3677 
True
1323 
ValueCountFrequency (%)
False 3677
73.5%
True 1323
 
26.5%
2023-03-25T09:36:39.628373image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

numbervmailmessages
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.7552
Minimum0
Maximum52
Zeros3678
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:39.768991image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q317
95-th percentile37
Maximum52
Range52
Interquartile range (IQR)17

Descriptive statistics

Standard deviation13.546393
Coefficient of variation (CV)1.7467497
Kurtosis0.19912718
Mean7.7552
Median Absolute Deviation (MAD)0
Skewness1.3504932
Sum38776
Variance183.50477
MonotonicityNot monotonic
2023-03-25T09:36:39.972109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 3678
73.6%
31 83
 
1.7%
28 67
 
1.3%
29 67
 
1.3%
33 66
 
1.3%
24 64
 
1.3%
27 64
 
1.3%
30 58
 
1.2%
26 58
 
1.2%
32 57
 
1.1%
Other values (38) 738
 
14.8%
ValueCountFrequency (%)
0 3678
73.6%
4 1
 
< 0.1%
6 2
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
10 4
 
0.1%
11 2
 
< 0.1%
12 11
 
0.2%
13 4
 
0.1%
14 9
 
0.2%
ValueCountFrequency (%)
52 1
 
< 0.1%
51 1
 
< 0.1%
50 2
 
< 0.1%
49 3
 
0.1%
48 5
 
0.1%
47 4
 
0.1%
46 8
0.2%
45 11
0.2%
44 9
0.2%
43 16
0.3%

totaldayminutes
Real number (ℝ)

Distinct1961
Distinct (%)39.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean180.2889
Minimum0
Maximum351.5
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:40.472092image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile91.7
Q1143.7
median180.1
Q3216.2
95-th percentile271.105
Maximum351.5
Range351.5
Interquartile range (IQR)72.5

Descriptive statistics

Standard deviation53.894699
Coefficient of variation (CV)0.2989352
Kurtosis-0.021294471
Mean180.2889
Median Absolute Deviation (MAD)36.3
Skewness-0.011730827
Sum901444.5
Variance2904.6386
MonotonicityNot monotonic
2023-03-25T09:36:40.676223image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189.3 10
 
0.2%
154 10
 
0.2%
159.5 9
 
0.2%
180 9
 
0.2%
184.5 9
 
0.2%
174.5 9
 
0.2%
177.1 9
 
0.2%
183.4 8
 
0.2%
189.8 8
 
0.2%
215.6 8
 
0.2%
Other values (1951) 4911
98.2%
ValueCountFrequency (%)
0 2
< 0.1%
2.6 1
< 0.1%
6.6 1
< 0.1%
7.2 1
< 0.1%
7.8 1
< 0.1%
7.9 1
< 0.1%
12.5 1
< 0.1%
17.6 1
< 0.1%
18.9 1
< 0.1%
19.5 1
< 0.1%
ValueCountFrequency (%)
351.5 1
< 0.1%
350.8 1
< 0.1%
346.8 1
< 0.1%
345.3 1
< 0.1%
338.4 1
< 0.1%
337.4 1
< 0.1%
335.5 1
< 0.1%
334.3 1
< 0.1%
332.9 1
< 0.1%
332.1 1
< 0.1%

totaldaycalls
Real number (ℝ)

Distinct123
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.0294
Minimum0
Maximum165
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:40.879345image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67
Q187
median100
Q3113
95-th percentile133
Maximum165
Range165
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.831197
Coefficient of variation (CV)0.19825369
Kurtosis0.17856779
Mean100.0294
Median Absolute Deviation (MAD)13
Skewness-0.084890964
Sum500147
Variance393.27639
MonotonicityNot monotonic
2023-03-25T09:36:41.082463image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 117
 
2.3%
102 113
 
2.3%
95 108
 
2.2%
94 104
 
2.1%
97 104
 
2.1%
100 102
 
2.0%
110 101
 
2.0%
112 101
 
2.0%
92 100
 
2.0%
108 100
 
2.0%
Other values (113) 3950
79.0%
ValueCountFrequency (%)
0 2
< 0.1%
30 1
 
< 0.1%
34 1
 
< 0.1%
35 1
 
< 0.1%
36 1
 
< 0.1%
39 2
< 0.1%
40 2
< 0.1%
42 2
< 0.1%
44 4
0.1%
45 3
0.1%
ValueCountFrequency (%)
165 1
 
< 0.1%
163 1
 
< 0.1%
160 2
 
< 0.1%
158 3
0.1%
157 2
 
< 0.1%
156 3
0.1%
152 2
 
< 0.1%
151 7
0.1%
150 6
0.1%
149 2
 
< 0.1%

totaldaycharge
Real number (ℝ)

Distinct1961
Distinct (%)39.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.649668
Minimum0
Maximum59.76
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:41.363703image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile15.59
Q124.43
median30.62
Q336.75
95-th percentile46.0905
Maximum59.76
Range59.76
Interquartile range (IQR)12.32

Descriptive statistics

Standard deviation9.1620687
Coefficient of variation (CV)0.29892881
Kurtosis-0.021165925
Mean30.649668
Median Absolute Deviation (MAD)6.17
Skewness-0.011729007
Sum153248.34
Variance83.943503
MonotonicityNot monotonic
2023-03-25T09:36:41.566821image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.18 10
 
0.2%
26.18 10
 
0.2%
27.12 9
 
0.2%
30.6 9
 
0.2%
31.37 9
 
0.2%
29.67 9
 
0.2%
30.11 9
 
0.2%
31.18 8
 
0.2%
32.27 8
 
0.2%
36.65 8
 
0.2%
Other values (1951) 4911
98.2%
ValueCountFrequency (%)
0 2
< 0.1%
0.44 1
< 0.1%
1.12 1
< 0.1%
1.22 1
< 0.1%
1.33 1
< 0.1%
1.34 1
< 0.1%
2.13 1
< 0.1%
2.99 1
< 0.1%
3.21 1
< 0.1%
3.32 1
< 0.1%
ValueCountFrequency (%)
59.76 1
< 0.1%
59.64 1
< 0.1%
58.96 1
< 0.1%
58.7 1
< 0.1%
57.53 1
< 0.1%
57.36 1
< 0.1%
57.04 1
< 0.1%
56.83 1
< 0.1%
56.59 1
< 0.1%
56.46 1
< 0.1%

totaleveminutes
Real number (ℝ)

Distinct1879
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200.63656
Minimum0
Maximum363.7
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:41.769938image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile118.495
Q1166.375
median201
Q3234.1
95-th percentile283.72
Maximum363.7
Range363.7
Interquartile range (IQR)67.725

Descriptive statistics

Standard deviation50.551309
Coefficient of variation (CV)0.25195462
Kurtosis0.051375131
Mean200.63656
Median Absolute Deviation (MAD)34
Skewness-0.011017695
Sum1003182.8
Variance2555.4348
MonotonicityNot monotonic
2023-03-25T09:36:41.957431image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
169.9 10
 
0.2%
199.7 10
 
0.2%
230.9 10
 
0.2%
167.6 9
 
0.2%
210.6 9
 
0.2%
216.5 9
 
0.2%
188.8 9
 
0.2%
187.5 9
 
0.2%
223.5 9
 
0.2%
194 9
 
0.2%
Other values (1869) 4907
98.1%
ValueCountFrequency (%)
0 1
< 0.1%
22.3 1
< 0.1%
31.2 1
< 0.1%
37.8 1
< 0.1%
41.7 1
< 0.1%
42.2 1
< 0.1%
42.5 1
< 0.1%
43.9 1
< 0.1%
47.3 2
< 0.1%
48.1 1
< 0.1%
ValueCountFrequency (%)
363.7 1
< 0.1%
361.8 1
< 0.1%
359.3 1
< 0.1%
354.2 1
< 0.1%
352.1 1
< 0.1%
351.6 1
< 0.1%
350.9 1
< 0.1%
350.5 1
< 0.1%
349.4 1
< 0.1%
348.9 1
< 0.1%

totalevecalls
Real number (ℝ)

Distinct126
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.191
Minimum0
Maximum170
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:42.191800image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67
Q187
median100
Q3114
95-th percentile133
Maximum170
Range170
Interquartile range (IQR)27

Descriptive statistics

Standard deviation19.826496
Coefficient of variation (CV)0.19788699
Kurtosis0.1173634
Mean100.191
Median Absolute Deviation (MAD)13
Skewness-0.020175203
Sum500955
Variance393.08994
MonotonicityNot monotonic
2023-03-25T09:36:42.379291image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 115
 
2.3%
97 110
 
2.2%
91 110
 
2.2%
94 106
 
2.1%
103 106
 
2.1%
101 104
 
2.1%
96 100
 
2.0%
104 100
 
2.0%
102 99
 
2.0%
98 99
 
2.0%
Other values (116) 3951
79.0%
ValueCountFrequency (%)
0 1
 
< 0.1%
12 1
 
< 0.1%
36 1
 
< 0.1%
37 1
 
< 0.1%
38 1
 
< 0.1%
42 1
 
< 0.1%
43 1
 
< 0.1%
44 2
 
< 0.1%
45 1
 
< 0.1%
46 5
0.1%
ValueCountFrequency (%)
170 1
 
< 0.1%
169 1
 
< 0.1%
168 1
 
< 0.1%
164 1
 
< 0.1%
159 1
 
< 0.1%
157 1
 
< 0.1%
156 1
 
< 0.1%
155 5
0.1%
154 4
0.1%
153 1
 
< 0.1%

totalevecharge
Real number (ℝ)

Distinct1659
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.054322
Minimum0
Maximum30.91
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:42.582410image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.0695
Q114.14
median17.09
Q319.9
95-th percentile24.112
Maximum30.91
Range30.91
Interquartile range (IQR)5.76

Descriptive statistics

Standard deviation4.2968433
Coefficient of variation (CV)0.2519504
Kurtosis0.051288785
Mean17.054322
Median Absolute Deviation (MAD)2.89
Skewness-0.010990328
Sum85271.61
Variance18.462862
MonotonicityNot monotonic
2023-03-25T09:36:42.769900image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.9 15
 
0.3%
14.25 15
 
0.3%
16.12 14
 
0.3%
18.79 13
 
0.3%
16.97 13
 
0.3%
18.96 13
 
0.3%
19.41 12
 
0.2%
17.09 11
 
0.2%
16.8 11
 
0.2%
18.62 11
 
0.2%
Other values (1649) 4872
97.4%
ValueCountFrequency (%)
0 1
< 0.1%
1.9 1
< 0.1%
2.65 1
< 0.1%
3.21 1
< 0.1%
3.54 1
< 0.1%
3.59 1
< 0.1%
3.61 1
< 0.1%
3.73 1
< 0.1%
4.02 2
< 0.1%
4.09 1
< 0.1%
ValueCountFrequency (%)
30.91 1
< 0.1%
30.75 1
< 0.1%
30.54 1
< 0.1%
30.11 1
< 0.1%
29.93 1
< 0.1%
29.89 1
< 0.1%
29.83 1
< 0.1%
29.79 1
< 0.1%
29.7 1
< 0.1%
29.66 1
< 0.1%

totalnightminutes
Real number (ℝ)

Distinct1853
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200.39162
Minimum0
Maximum395
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:42.973018image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile117.395
Q1166.9
median200.4
Q3234.7
95-th percentile283.405
Maximum395
Range395
Interquartile range (IQR)67.8

Descriptive statistics

Standard deviation50.527789
Coefficient of variation (CV)0.25214522
Kurtosis0.082359197
Mean200.39162
Median Absolute Deviation (MAD)33.8
Skewness0.019324917
Sum1001958.1
Variance2553.0575
MonotonicityNot monotonic
2023-03-25T09:36:43.176136image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188.2 11
 
0.2%
194.3 11
 
0.2%
186.2 11
 
0.2%
214.6 10
 
0.2%
208.9 10
 
0.2%
228.1 10
 
0.2%
210 9
 
0.2%
192.7 9
 
0.2%
193.6 9
 
0.2%
214.7 9
 
0.2%
Other values (1843) 4901
98.0%
ValueCountFrequency (%)
0 1
< 0.1%
23.2 1
< 0.1%
43.7 1
< 0.1%
45 1
< 0.1%
46.7 1
< 0.1%
47.4 1
< 0.1%
50.1 2
< 0.1%
50.9 1
< 0.1%
53.3 1
< 0.1%
54 1
< 0.1%
ValueCountFrequency (%)
395 1
< 0.1%
381.9 1
< 0.1%
381.6 1
< 0.1%
377.5 1
< 0.1%
367.7 1
< 0.1%
364.9 1
< 0.1%
364.3 1
< 0.1%
359.9 1
< 0.1%
355.1 1
< 0.1%
354.9 1
< 0.1%

totalnightcalls
Real number (ℝ)

Distinct131
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.9192
Minimum0
Maximum175
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:43.363630image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile67
Q187
median100
Q3113
95-th percentile132
Maximum175
Range175
Interquartile range (IQR)26

Descriptive statistics

Standard deviation19.958686
Coefficient of variation (CV)0.19974826
Kurtosis0.14443808
Mean99.9192
Median Absolute Deviation (MAD)13
Skewness0.0021328427
Sum499596
Variance398.34914
MonotonicityNot monotonic
2023-03-25T09:36:43.551124image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105 121
 
2.4%
102 109
 
2.2%
100 108
 
2.2%
104 106
 
2.1%
99 105
 
2.1%
103 104
 
2.1%
91 103
 
2.1%
94 103
 
2.1%
95 102
 
2.0%
98 102
 
2.0%
Other values (121) 3937
78.7%
ValueCountFrequency (%)
0 1
 
< 0.1%
12 1
 
< 0.1%
33 1
 
< 0.1%
36 1
 
< 0.1%
38 2
< 0.1%
40 1
 
< 0.1%
41 1
 
< 0.1%
42 4
0.1%
43 1
 
< 0.1%
44 1
 
< 0.1%
ValueCountFrequency (%)
175 1
< 0.1%
170 1
< 0.1%
168 1
< 0.1%
166 1
< 0.1%
165 1
< 0.1%
164 1
< 0.1%
161 1
< 0.1%
160 1
< 0.1%
159 2
< 0.1%
158 2
< 0.1%

totalnightcharge
Real number (ℝ)

Distinct1028
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.017732
Minimum0
Maximum17.77
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:43.754240image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.28
Q17.51
median9.02
Q310.56
95-th percentile12.7505
Maximum17.77
Range17.77
Interquartile range (IQR)3.05

Descriptive statistics

Standard deviation2.2737627
Coefficient of variation (CV)0.25214352
Kurtosis0.082377615
Mean9.017732
Median Absolute Deviation (MAD)1.52
Skewness0.019286744
Sum45088.66
Variance5.1699966
MonotonicityNot monotonic
2023-03-25T09:36:44.019856image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9.66 19
 
0.4%
8.47 19
 
0.4%
10.8 18
 
0.4%
9.63 18
 
0.4%
8.15 18
 
0.4%
9.4 18
 
0.4%
10.26 18
 
0.4%
9.45 17
 
0.3%
10.49 17
 
0.3%
10.35 16
 
0.3%
Other values (1018) 4822
96.4%
ValueCountFrequency (%)
0 1
< 0.1%
1.04 1
< 0.1%
1.97 1
< 0.1%
2.03 1
< 0.1%
2.1 1
< 0.1%
2.13 1
< 0.1%
2.25 2
< 0.1%
2.29 1
< 0.1%
2.4 1
< 0.1%
2.43 1
< 0.1%
ValueCountFrequency (%)
17.77 1
< 0.1%
17.19 1
< 0.1%
17.17 1
< 0.1%
16.99 1
< 0.1%
16.55 1
< 0.1%
16.42 1
< 0.1%
16.39 1
< 0.1%
16.2 1
< 0.1%
15.98 1
< 0.1%
15.97 1
< 0.1%

totalintlminutes
Real number (ℝ)

Distinct170
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.26178
Minimum0
Maximum20
Zeros24
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:44.238601image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.7
Q18.5
median10.3
Q312
95-th percentile14.7
Maximum20
Range20
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.7613957
Coefficient of variation (CV)0.2690952
Kurtosis0.65531661
Mean10.26178
Median Absolute Deviation (MAD)1.8
Skewness-0.20996629
Sum51308.9
Variance7.6253063
MonotonicityNot monotonic
2023-03-25T09:36:45.113567image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.1 90
 
1.8%
9.8 88
 
1.8%
11.3 83
 
1.7%
11.4 81
 
1.6%
10.1 81
 
1.6%
10.9 80
 
1.6%
9.7 79
 
1.6%
10.6 78
 
1.6%
11 78
 
1.6%
10.5 78
 
1.6%
Other values (160) 4184
83.7%
ValueCountFrequency (%)
0 24
0.5%
0.4 1
 
< 0.1%
1.1 2
 
< 0.1%
1.3 1
 
< 0.1%
2 3
 
0.1%
2.1 2
 
< 0.1%
2.2 2
 
< 0.1%
2.4 1
 
< 0.1%
2.5 1
 
< 0.1%
2.6 1
 
< 0.1%
ValueCountFrequency (%)
20 1
< 0.1%
19.7 2
< 0.1%
19.3 1
< 0.1%
19.2 1
< 0.1%
18.9 2
< 0.1%
18.7 1
< 0.1%
18.5 1
< 0.1%
18.4 1
< 0.1%
18.3 1
< 0.1%
18.2 2
< 0.1%

totalintlcalls
Real number (ℝ)

Distinct21
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4352
Minimum0
Maximum20
Zeros24
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:45.347935image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q36
95-th percentile9
Maximum20
Range20
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4567882
Coefficient of variation (CV)0.55392951
Kurtosis3.2681836
Mean4.4352
Median Absolute Deviation (MAD)1
Skewness1.3606925
Sum22176
Variance6.0358081
MonotonicityNot monotonic
2023-03-25T09:36:45.535428image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3 992
19.8%
4 953
19.1%
2 743
14.9%
5 706
14.1%
6 495
9.9%
7 308
 
6.2%
1 265
 
5.3%
8 172
 
3.4%
9 148
 
3.0%
10 76
 
1.5%
Other values (11) 142
 
2.8%
ValueCountFrequency (%)
0 24
 
0.5%
1 265
 
5.3%
2 743
14.9%
3 992
19.8%
4 953
19.1%
5 706
14.1%
6 495
9.9%
7 308
 
6.2%
8 172
 
3.4%
9 148
 
3.0%
ValueCountFrequency (%)
20 1
 
< 0.1%
19 2
 
< 0.1%
18 4
 
0.1%
17 2
 
< 0.1%
16 7
 
0.1%
15 9
 
0.2%
14 6
 
0.1%
13 19
0.4%
12 23
0.5%
11 45
0.9%

totalintlcharge
Real number (ℝ)

Distinct170
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.771196
Minimum0
Maximum5.4
Zeros24
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:45.738547image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.54
Q12.3
median2.78
Q33.24
95-th percentile3.97
Maximum5.4
Range5.4
Interquartile range (IQR)0.94

Descriptive statistics

Standard deviation0.74551371
Coefficient of variation (CV)0.26902237
Kurtosis0.65598855
Mean2.771196
Median Absolute Deviation (MAD)0.48
Skewness-0.21028611
Sum13855.98
Variance0.55579069
MonotonicityNot monotonic
2023-03-25T09:36:45.941663image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 90
 
1.8%
2.65 88
 
1.8%
3.05 83
 
1.7%
3.08 81
 
1.6%
2.73 81
 
1.6%
2.94 80
 
1.6%
2.62 79
 
1.6%
2.86 78
 
1.6%
2.97 78
 
1.6%
2.84 78
 
1.6%
Other values (160) 4184
83.7%
ValueCountFrequency (%)
0 24
0.5%
0.11 1
 
< 0.1%
0.3 2
 
< 0.1%
0.35 1
 
< 0.1%
0.54 3
 
0.1%
0.57 2
 
< 0.1%
0.59 2
 
< 0.1%
0.65 1
 
< 0.1%
0.68 1
 
< 0.1%
0.7 1
 
< 0.1%
ValueCountFrequency (%)
5.4 1
< 0.1%
5.32 2
< 0.1%
5.21 1
< 0.1%
5.18 1
< 0.1%
5.1 2
< 0.1%
5.05 1
< 0.1%
5 1
< 0.1%
4.97 1
< 0.1%
4.94 1
< 0.1%
4.91 2
< 0.1%
Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5704
Minimum0
Maximum9
Zeros1023
Zeros (%)20.5%
Negative0
Negative (%)0.0%
Memory size39.2 KiB
2023-03-25T09:36:46.113532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3063633
Coefficient of variation (CV)0.83186662
Kurtosis1.4810955
Mean1.5704
Median Absolute Deviation (MAD)1
Skewness1.0424623
Sum7852
Variance1.7065852
MonotonicityNot monotonic
2023-03-25T09:36:46.285401image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 1786
35.7%
2 1127
22.5%
0 1023
20.5%
3 665
 
13.3%
4 252
 
5.0%
5 96
 
1.9%
6 34
 
0.7%
7 13
 
0.3%
9 2
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
0 1023
20.5%
1 1786
35.7%
2 1127
22.5%
3 665
 
13.3%
4 252
 
5.0%
5 96
 
1.9%
6 34
 
0.7%
7 13
 
0.3%
8 2
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
9 2
 
< 0.1%
8 2
 
< 0.1%
7 13
 
0.3%
6 34
 
0.7%
5 96
 
1.9%
4 252
 
5.0%
3 665
 
13.3%
2 1127
22.5%
1 1786
35.7%
0 1023
20.5%

Interactions

2023-03-25T09:36:35.359598image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:55.515074image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:58.372618image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:01.020036image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:03.896204image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:06.565230image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:09.341234image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:12.154139image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:15.026494image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:17.714022image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:20.759618image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:23.454977image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:26.703379image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:29.863390image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:32.686245image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:35.522148image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:55.771071image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:58.540558image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:01.201091image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:04.065453image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:06.865060image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:09.559906image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:12.324910image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:15.192892image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:17.894564image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:20.933276image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:23.626099image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:26.921522image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:30.037466image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:32.849668image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:35.698919image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:55.934112image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:58.712982image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:01.376989image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:04.263582image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:07.040578image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:09.745648image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:12.499968image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:15.368912image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:18.066654image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:21.112764image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:23.798277image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:27.139609image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:30.215108image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:33.021025image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:35.892834image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:56.111280image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:58.890370image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:01.566655image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:04.441532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:07.214533image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:09.931951image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:12.844896image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:15.554058image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:18.259990image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:21.295666image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:23.986408image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:27.334856image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:30.410377image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:33.194751image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:36.068694image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:56.279513image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:59.060756image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:01.743191image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:04.620888image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:07.386497image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:10.114138image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:13.018814image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:15.725884image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:18.436668image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:21.471294image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:24.169299image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:27.522946image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:30.588231image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:33.375271image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:36.249917image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:56.451692image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:59.230224image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:02.029198image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:04.789428image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:07.557621image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:10.296399image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:13.200337image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:15.902733image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:18.618731image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:21.643697image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:24.345448image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:27.706373image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:30.772568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:33.548457image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:36.434277image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:56.620009image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:59.412476image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:02.207446image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:04.967659image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:07.737642image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:10.485556image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:13.379669image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:16.084465image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:18.801234image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:21.831404image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:24.527254image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:27.913002image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:30.958399image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:33.724150image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:36.601623image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:56.801296image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:59.588360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:02.392707image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:05.151611image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:07.914965image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:10.671356image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:13.566810image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:16.257897image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:18.990152image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:22.005759image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:24.766948image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:28.102625image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:31.145900image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:33.921957image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:36.770502image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:56.972504image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:59.759435image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:02.571831image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:05.319055image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:08.085132image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:10.858114image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:13.744847image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:16.441054image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:19.173724image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:22.185018image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:25.010997image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:28.284163image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:31.327450image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:34.094250image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:36.950341image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:57.179455image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:59.947509image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:02.759958image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:05.503721image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:08.269976image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:11.045144image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:13.931840image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:16.619789image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:19.367060image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:22.372554image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:25.337787image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:28.492924image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:31.534732image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:34.269026image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:37.185052image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:57.402555image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:00.126682image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:02.941530image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:05.680272image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:08.455379image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:11.228585image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:14.118190image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:16.815911image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:19.629061image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:22.552405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:25.616766image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:28.681966image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:31.736285image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:34.447895image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:37.363681image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:57.590157image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:00.307175image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:03.134227image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:05.858395image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:08.634327image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:11.420549image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:14.306829image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:16.995528image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:19.822679image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:22.733783image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:25.847213image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:28.872866image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:31.944229image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:34.625973image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:37.547792image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:57.771836image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:00.496769image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:03.322143image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:06.042802image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:08.819848image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:11.612781image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:14.501816image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:17.193375image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:20.218708image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:22.922839image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:26.073798image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:29.069757image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:32.138804image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:34.809625image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:37.736589image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:58.039486image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:00.682056image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:03.557877image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:06.232460image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:09.005413image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:11.802602image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:14.689068image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:17.379081image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:20.406567image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:23.109538image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:26.290411image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:29.262548image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:32.337278image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:34.989340image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:37.903697image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:35:58.206861image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:00.849775image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:03.723965image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:06.398424image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:09.174679image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:11.976166image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:14.859552image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:17.545905image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:20.588379image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:23.288237image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:26.521127image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:29.687953image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:32.515523image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2023-03-25T09:36:35.151396image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2023-03-25T09:36:46.457268image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
accountlengthnumbervmailmessagestotaldayminutestotaldaycallstotaldaychargetotaleveminutestotalevecallstotalevechargetotalnightminutestotalnightcallstotalnightchargetotalintlminutestotalintlcallstotalintlchargenumbercustomerservicecallschurninternationalplanvoicemailplan
accountlength1.000-0.0100.0050.0250.005-0.0120.008-0.0120.000-0.0060.0000.0060.0180.006-0.0080.0000.0000.000
numbervmailmessages-0.0101.0000.009-0.0040.0090.024-0.0020.0240.0000.0070.0000.002-0.0100.002-0.0120.1090.0000.998
totaldayminutes0.0050.0091.0000.0061.000-0.0110.008-0.0110.0030.0030.003-0.023-0.006-0.023-0.0010.3620.0380.031
totaldaycalls0.025-0.0040.0061.0000.0060.0020.0110.0020.003-0.0040.0020.0070.0090.007-0.0140.0270.0000.000
totaldaycharge0.0050.0091.0000.0061.000-0.0110.008-0.0110.0030.0030.003-0.023-0.006-0.023-0.0010.3620.0380.032
totaleveminutes-0.0120.024-0.0110.002-0.0111.0000.0021.000-0.0160.014-0.0160.0090.0110.009-0.0180.0830.0000.037
totalevecalls0.008-0.0020.0080.0110.0080.0021.0000.0020.008-0.0160.008-0.0110.006-0.0110.0120.0000.0000.000
totalevecharge-0.0120.024-0.0110.002-0.0111.0000.0021.000-0.0160.014-0.0160.0090.0110.009-0.0180.0830.0000.038
totalnightminutes0.0000.0000.0030.0030.003-0.0160.008-0.0161.0000.0171.000-0.007-0.013-0.007-0.0150.0370.0460.010
totalnightcalls-0.0060.0070.003-0.0040.0030.014-0.0160.0140.0171.0000.0170.005-0.0000.005-0.0010.0000.0000.000
totalnightcharge0.0000.0000.0030.0020.003-0.0160.008-0.0161.0000.0171.000-0.007-0.013-0.007-0.0150.0370.0450.010
totalintlminutes0.0060.002-0.0230.007-0.0230.009-0.0110.009-0.0070.005-0.0071.0000.0061.000-0.0160.0580.0000.000
totalintlcalls0.018-0.010-0.0060.009-0.0060.0110.0060.011-0.013-0.000-0.0130.0061.0000.006-0.0110.0790.0000.000
totalintlcharge0.0060.002-0.0230.007-0.0230.009-0.0110.009-0.0070.005-0.0071.0000.0061.000-0.0160.0580.0000.000
numbercustomerservicecalls-0.008-0.012-0.001-0.014-0.001-0.0180.012-0.018-0.015-0.001-0.015-0.016-0.011-0.0161.0000.3120.0220.018
churn0.0000.1090.3620.0270.3620.0830.0000.0830.0370.0000.0370.0580.0790.0580.3121.0000.2580.109
internationalplan0.0000.0000.0380.0000.0380.0000.0000.0000.0460.0000.0450.0000.0000.0000.0220.2581.0000.000
voicemailplan0.0000.9980.0310.0000.0320.0370.0000.0380.0100.0000.0100.0000.0000.0000.0180.1090.0001.000

Missing values

2023-03-25T09:36:38.166531image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-03-25T09:36:38.582738image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

churnaccountlengthinternationalplanvoicemailplannumbervmailmessagestotaldayminutestotaldaycallstotaldaychargetotaleveminutestotalevecallstotalevechargetotalnightminutestotalnightcallstotalnightchargetotalintlminutestotalintlcallstotalintlchargenumbercustomerservicecalls
0No128noyes25265.111045.07197.49916.78244.79111.0110.032.701
1No107noyes26161.612327.47195.510316.62254.410311.4513.733.701
2No137nono0243.411441.38121.211010.30162.61047.3212.253.290
3No84yesno0299.47150.9061.9885.26196.9898.866.671.782
4No75yesno0166.711328.34148.312212.61186.91218.4110.132.733
5No118yesno0223.49837.98220.610118.75203.91189.186.361.700
6No121noyes24218.28837.09348.510829.62212.61189.577.572.033
7No147yesno0157.07926.69103.1948.76211.8969.537.161.920
8No117nono0184.59731.37351.68029.89215.8909.718.742.351
9No141yesyes37258.68443.96222.011118.87326.49714.6911.253.020
churnaccountlengthinternationalplanvoicemailplannumbervmailmessagestotaldayminutestotaldaycallstotaldaychargetotaleveminutestotalevecallstotalevechargetotalnightminutestotalnightcallstotalnightchargetotalintlminutestotalintlcallstotalintlchargenumbercustomerservicecalls
4990Yes140nono0244.711541.60258.610121.98231.311210.417.562.031
4991Yes97nono0252.68942.94340.39128.93256.56711.548.852.381
4992No83nono0188.37032.01243.88820.72213.7799.6210.362.780
4993No73nono0177.98930.24131.28211.15186.2898.3811.563.113
4994No75nono0170.710129.02193.112616.41129.11045.816.971.861
4995No50noyes40235.712740.07223.012618.96297.511613.399.952.672
4996Yes152nono0184.29031.31256.87321.83213.61139.6114.723.973
4997No61nono0140.68923.90172.812814.69212.4979.5613.643.671
4998No109nono0188.86732.10171.79214.59224.48910.108.562.300
4999No86noyes34129.410222.00267.110422.70154.81006.979.3162.510